• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.11
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• pp.2727-2732
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• 2014

Recently, the researches of object tracking and recognition using Microsoft's Kinect are being actively studied. In this environment human hand detection and tracking is the most basic technique for human computer interaction. This paper proposes a method of improving the accuracy of the detected hand region's boundary in the cluttered background. To do this, we combine the hand detection results using the skin color with the extracted depth image from Kinect. From the experimental results, we show that the proposed method increase the accuracy of the hand region detection than the method of detecting a hand region with a depth image only. If the proposed method is applied to the sign language or gesture recognition system it is expected to contribute much to accuracy improvement.

• Journal of Korea Multimedia Society
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• v.15 no.4
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• pp.501-507
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• 2012

Human body motion is a non-verbal part for interaction or movement that can be used to involves real world and virtual world. In this paper, we explain a study on natural user interface (NUI) in human hand motion recognition using RGB color information and depth information by Kinect camera from Microsoft Corporation. To achieve the goal, hand tracking and gesture recognition have no major dependencies of the work environment, lighting or users' skin color, libraries of particular use for natural interaction and Kinect device, which serves to provide RGB images of the environment and the depth map of the scene were used. An improved Camshift tracking algorithm is used to tracking hand motion, the experimental results show out it has better performance than Camshift algorithm, and it has higher stability and accuracy as well.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.10
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• pp.1892-1897
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• 2017

This paper proposes a finger counting algorithm for a hand with stuck fingers. The proposed algorithm is based on the fact that straight line type shadows are inevitably generated between fingers. It divides the hand region into the thumb region and the four fingers region for effective shadow detection, and generates an edge image in each region. Projection curves are generated by appling a line detection and a projection technique to each edge image, and the peaks of the curves are detected as candidates for finger shadows. And then peaks due to finger shadows are extracted from them and counted. In the finger counting experiment on hand images expressing various shapes with stuck fingers, the counting success rate is from 83.3% to 100% according to the number of fingers, and 93.1% on the whole. It also shows that if hand images are generated under controlled conditions, the failure cases can be sufficiently improved.

• Journal of Korea Multimedia Society
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• v.8 no.6
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• pp.768-775
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• 2005

For sign languages are main communication means among hearing-impaired people, there are communication difficulties between speaking-oriented people and sign-language-oriented people. Automated sign-language recognition may resolve these communication problems. In sign languages, finger spelling is used to spell names and words that are not listed in the dictionary. There have been research activities for gesture and posture recognition using glove-based devices. However, these devices are often expensive, cumbersome, and inadequate for recognizing elaborate finger spelling. Use of colored patches or gloves also cause uneasiness. In this paper, a vision-based finger spelling recognition system is introduced. In our method, captured hand region images were separated from the background using a skin detection algorithm assuming that there are no skin-colored objects in the background. Then, hand postures were recognized using a two-dimensional grid analysis method. Our recognition system is not sensitive to the size or the rotation of the input posture images. By optimizing the weights of the posture features using a genetic algorithm, our system achieved high accuracy that matches other systems using devices or colored gloves. We applied our posture recognition system for detecting Korean Sign Language, achieving better than $93\%$ accuracy.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2016.11a
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• pp.146-147
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• 2016

손동작 인식은 대부분 스킨 컬러 검출을 이용하였다. 하지만 이와 같은 방법으로는 빛이나 주변 사물에 의해 영향을 많이 받기 때문에 정확한 값을 일정하게 도출 해낼 수 없었다. 이에 본 논문은 운동축적 기법을 이용하여 움직임을 파악한 후 손의 움직임을 트랙킹하여 운동 방향을 구한다. 제안된 시스템은 C/C++을 기반으로 구현하여, 실험에서 제안 방법이 안정적이고 우수한 성능을 보여줌을 증명하였다.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.47 no.3
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• pp.1-10
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• 2010

As various interfacing devices for computational machines are being developed, a new HCI method using hand motion input is introduced. This interface method is a vision-based approach using a single camera for detecting and tracking hand movements. In the previous researches, only a skin color is used for detecting and tracking hand location. However, in our design, skin color and shape information are collectively considered. Consequently, detection ability of a hand increased. we proposed primary orientation edge descriptor for getting an edge information. This method uses only one hand model. Therefore, we do not need training processing time. This system consists of a detecting part and a tracking part for efficient processing. In tracking part, the system is quite robust on the orientation of the hand. The system is applied to recognize a hand written number in script style using DNAC algorithm. Performance of the proposed algorithm reaches 82% recognition ratio in detecting hand region and 90% in recognizing a written number in script style.

• Journal of Korea Society of Industrial Information Systems
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• v.24 no.5
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• pp.129-137
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• 2019

Ubiquitous computing technology is emerging as information technology advances. In line with this, a number of studies are being carried out to increase device miniaturization and user convenience. Some of the proposed devices are user-friendly and uncomfortable with hand-held operation. To address these inconveniences, this paper proposed a virtual button that could be used in watching television. When watching a video on television, a camera is installed at the top of the TV, using the fact that the user watches the video from the front, so that the camera takes a picture of the top of the head. Extract the background and hand area separately from the filmed image, extract the outline to the extracted hand area, and detect the tip point of the finger. Detection of the end point of the finger produces a virtual button interface at the top of the image being filmed in front, and the button activates when the end point of the detected finger becomes a pointer and is located inside the button.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2014.06a
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• pp.34-35
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• 2014

본 논문에서는 손가락 제스처 인식을 위해서 깊이 영상 카메라를 이용하여 손 영역을 추적하고 손가락 끝점을 찾는 방법을 제시하고자 한다. 실시간 영역 추적을 위해 적은 연산량으로 손 영역의 중심점을 검출하고 추적이 가능하여야 하며, 다양한 제스처를 효과적으로 인식하기 위해서는 손 모양에서 손가락을 인식하여야 하기 때문에 손가락 끝점을 찾는 방법도 함꼐 제시하고자 한다. 또한 손가락이 정확히 검출되었는지를 확인하기 위해서 손가락의 이동과 손가락의 클릭 제스처를 마우스에 연동하여 검출 결과를 테스트 하였다.

• Korean Journal of Cognitive Science
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• v.8 no.4
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• pp.35-53
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• 1997

본 논문은 컴퓨터 시각을 이용하여 제스처를 인식함으로써 사용자에게 보다 편리한 인터페이스를 제공하는 것을 목표로 한다. 제안하는 제스처 인식 방법은 손영역을 획득하는 손영역 획득 모듈？손영역을 인식하는 인식 모듈로 나누어 수행한다. 손영역 획득 모듈에서는 손색상 모델？손색상 결정함수를 정의하여 칼라영상의 영역 분리를 수행하였고, 칼만필터를 이용하여 손색상 모델을 갱신하고 탐색영역을 제한하여 영역 추적을 용이하게 하였다. 영역 추적은 전 시점의 손영역 정보를 이용하여 현 시점의 손영역을 획득한다. 인식 모듈에서는 정적인 제스처를 표현하는 객체 프레임？행동 프레임, 그리고 동적인 제스처를 표현하는 스키마를 정의한다. 그리고 획득된 손영역？정합을 수행함으로써 제스처를 인식한다. 실험 결갬灌？제안하는 제스처 기반 인터페이스를 적용한 삼목(Tic-Tac-Toe) 게임 프로그램을 구현하였다. 사용자는 제스처를 이용하여 컴퓨터와 게임을 진행한다. 제안하는 시스템은 다른 종류의 게임 프로그램이나 마우스의 역할을 수행하는 윈도우 시스템의 제어, 그리고 가상 현실 시스템에 적용될 수 있다.

• 한국HCI학회:학술대회논문집
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• 2008.02b
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• pp.60-63
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• 2008

The sony Eytoy is developed on Playstation 2 using webcam for detecting human. A user see his appearance in television and become real gamer in the game. It is very different interface compared with ordinary video game which uses joystick. Although Eyetoy already was made for commercial products but the interface method still is interesting and can be added with many techniques like gesture recognition. In this paper, we have developed game interface with image processing for human hand and face detection and with game graphic module. And we realize one example game for busting balloons and demonstrated the game interface abilities. We will open this project for other developers and will be developed very much.